MétaCan
Menu
← Back to cohort
Record W2335855422 · doi:10.1149/ma2014-01/18/802

Mechanical Damage Propagation in Polymer Electrolyte Membrane Fuel Cells Under Humidity and Temperature Cycles

2014· article· en· W2335855422 on OpenAlexaff
Roshanak Banan, Jean W. Zu, Aimy Bazylak

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProton exchange membrane fuel cellMaterials scienceElectrolyteComposite materialRelative humidityPolymerMembrane electrode assemblyNafionHumidityChemical engineeringElectrodeFuel cellsChemistryElectrochemistry

Abstract

fetched live from OpenAlex

Significant advancements have been made in polymer electrolyte membrane fuel cell (PEMFC) technologies over the past decade in areas such as water management, thermal management and electrocatalysis. However, challenges still remain in the area of mechanical degradation [1]. Reported mechanical damage in PEMFCs includes cracks and delaminations (separation of the layers) in the membrane electrode assembly (MEA), pore size distribution changes in the porous layers, and fractures in the gas diffusion layer (GDL) [2–4]. Such mechanical damage can lead to fuel crossover, performance degradation, and reduced durability [5]. Therefore, it is necessary to identify and control the mechanisms that are involved in damage initiation and propagation in the PEMFC. Mechanical stresses induced by temperature and relative humidity cycles during PEMFC operation play an important role in the initiation and evolution of mechanical damage in the MEA [6]. The PEMFC is particularly susceptible to damage in transportation applications, where the fuel cell is subjected to a high number of start-up/shut down cycles and hence a higher number of humidity and temperature variations compared with stationary applications [7] To the authors’ best knowledge, there is a scarcity in the number of studies regarding mechanical damage evolution in PEMFCs due to humidity and temperature variation [3,4]. Rong et al. [4] modeled a three-phase microstructure including Nafion, a carbon/platinum (C/Pt) agglomerate and a pore. They found that frequent start-up and shutdown cycles of fuel cells leads to earlier initiations of damage at the catalyst layer (CL)/membrane and GDL/CL interfaces. Poornesh et al. [3] investigated the effect of the CL material properties on the crack propagation in the MEA. These valuable studies have provided insight into the mechanical damage evolution in PEMFCs; however, the geometry of the modeled crack and the applied loading regime in their studies are idealized and do not represent the real critical situation in PEMFCs. The goal of this work is to establish a comprehensive numerical model to study the delamination and crack evolution in PEMFCs. A finite element (FE) model based on the cohesive zone theory [8] is employed to describe the delamination propagation at the membrane/CL interface due to duty cycles. Furthermore, the effects of the alignment of the bipolar plates (alternating and aligned gas channels), frequency and the number of humidity and temperature cycles, and the initial length of the delmaination on the damage propagation pattern are investigated. The employed FE model includes two bipolar plates, two GDLs, two CLs, a Nafion membrane, and a delamination, as shown in Figure 1. In order to simulate the loading condition in a working PEMFC, cycles of humidity and temperature are applied to the model as shown in Figure 2. The humidity increases from 30% to 95%, while the temperature increases from 20 0C to 86 0C[6]. This work provides insight into the importance of considering mechanical damage to the MEA under working conditions in transportation applications. References [1] The Department of Energy Hydrogen and Fuel Cells Program Plan - Draft. 2010, pp. 1–105. [2] S. Kim, B. K. Ahn, and M. M. Mench, Journal of Power Sources, vol. 179, no. 1, pp. 140–146, 2008. [3] K. K. Poornesh, C. D. Cho, G. B. Lee, and Y. S. Tak, Journal of Power Sources, vol. 195, no. 9, pp. 2718–2730, 2010. [4] F. Rong, C. Huang, Z. Liu, D. Song, and Q. Wang, Journal of Power Sources, vol. 175, no. 2, pp. 699–711, 2008. [5] G. Diloyan, M. Sobel, K. Das, and P. Hutapea, Journal of Power Sources, vol. 214, pp. 59–67, Sep. 2012. [6] A. Kusoglu, A. M. Karlsson, M. H. Santare, S. Cleghorn, and W. B. Johnson, Journal of Power Sources, vol. 170, no. 2, pp. 345–358, Jul. 2007. [7] Y. Tang, M. Santare, and A. Karlsson, Journal Of Fuel Cell Science And Technology, vol. 3, 2006. [8] A. Turon, J. Costa, P. P. Camanho, and C. G. Dávila, Composites Part A, vol. 38, no. 11, pp. 2270–2282, Nov. 2007.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.193
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting Abstracts→Same topicFuel Cells and Related Materials→French-language works237,207→